Hamdy Mubarak · page 2
Papers
- Arabic POS Tagging: Don't Abandon Feature Engineering Just Yet (2017 · 47 citations)
The paper asks whether hand-crafted linguistic features are still useful for Arabic part-of-speech tagging now that bi-LSTM taggers with embeddings can learn representations directly from data. - ASAD: Arabic Social media Analytics and unDerstanding (2021 · 42 citations)
Arabic Twitter content is rich in dialects and informal language, yet few public tools analyse it, and those that exist are scattered or trained on non-Twitter data. - ALT Submission for OSACT Shared Task on Offensive Language Detection (2020 · 39 citations)
The ALT team from Qatar Computing Research Institute entered the OSACT4 shared task on Arabic tweets. The task had two parts: flagging offensive language (Subtask A) and flagging hate speech (Subtask B). The organizers supplied 10,000 labelled tweets with a strong class imbalance: about 19% are offensive and only… - Learning from Relatives: Unified Dialectal Arabic Segmentation (2017 · 37 citations)
Social-media Arabic is mostly written in regional dialects. Earlier segmenters were built for one dialect at a time, so text first had to pass through dialect identification, which can be less than 90% accurate. The authors ask two questions: how well does a segmenter trained on one dialect handle the others, and can… - Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging (2014 · 37 citations)
The paper builds an end-to-end Arabic pipeline: correction of common spelling confusions (alef forms, ta marbuta and ha, alef maqsura and ya), character-level segmentation with a CRF, POS tagging with a CRF, and gender and number tagging for nouns and adjectives. - ALT at SemEval-2020 Task 12: Arabic and English Offensive Language Identification in Social Media (2020 · 35 citations)
The paper reports the ALT team's entry for sub-task A of SemEval-2020 Task 12, which asks whether a tweet is offensive (OFF) or not (NOT). - So Hateful! Building a Multi-Label Hate Speech Annotated Arabic Dataset (2024 · 33 citations)
The paper addresses the lack of large, richly labelled Arabic resources for detecting hate speech on social media. - Advances in dialectal Arabic speech recognition: a study using Twitter to improve Egyptian ASR (2014 · 32 citations)
The paper tackles automatic speech recognition for Egyptian Arabic. This dialect lacks a fixed spelling standard and has very little transcribed audio. The authors used about 12.5 hours of Egyptian speech drawn from a larger 200-hour Aljazeera broadcast collection: 10 hours for acoustic training and 1.25 hours each… - Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model (2020 · 29 citations)
Arabic is usually written without short vowels (diacritics), so readers must supply them to pronounce words and resolve meaning. - Build Fast and Accurate Lemmatization for Arabic (2018 · 26 citations)
Arabic lemmatization differs from surface stemming: it must restore the citation form, which can require changing stem patterns, not only cutting affixes. - Part-of-Speech Tagging for Arabic Gulf Dialect Using Bi-LSTM (2018 · 26 citations)
Standard Arabic taggers break down on dialectal social-media text, and Gulf Arabic had no dedicated tagger at all, although it is widely used online. - Automatic Correction of Arabic Text: a Cascaded Approach (2014 · 25 citations)
The paper describes QCRI's entry in the QALB-2014 shared task on automatically correcting Arabic text, using the QALB dataset. - PalmX 2025: The First Shared Task on Benchmarking LLMs on Arabic and Islamic Culture (2025 · 23 citations)
Large language models learn mostly from web data, which leans toward Western, high-resource cultures. As a result, they understand Arab and Islamic customs, history and religious practice poorly, and there was no common yardstick to measure this. PalmX 2025 is a shared task built to fill that gap. It is divided into… - IslamicEval 2025: The First Shared Task of Capturing LLMs Hallucination in Islamic Content (2025 · 19 citations)
LLMs used for Arabic religious questions often misquote or invent Qur'anic verses and Hadiths. IslamicEval 2025 is the first shared task built around measuring and catching such errors. It has two parts. - A System for Diacritizing Four Varieties of Arabic (2019 · 17 citations)
Arabic is usually written without short vowels (diacritics). Readers must infer them to pronounce words, so automatic diacritic restoration matters for text-to-speech and language learning. This demo paper presents a deployed system that adds diacritics back for four varieties: Classical Arabic (CA), Modern Standard… - NatiQ: An End-to-end Text-to-Speech System for Arabic (2022 · 16 citations)
The paper presents NatiQ, a web-deployed Arabic text-to-speech system. Arabic is a hard case for TTS because ordinary text leaves out short vowels, so the pronunciation has to be reconstructed before synthesis. The authors recorded two in-house corpora at 44kHz. "Amina" is an expressive female voice reading… - Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM (2017 · 16 citations)
The paper segments four Arabic dialects (Egyptian, Levantine, Gulf, Maghrebi) from raw Twitter text. Only about 350 manually segmented tweets per dialect are used for training, with 5-fold cross-validation and a 70/10/20 split. Two approaches are compared. An SVM ranker generates all segmentations of a word from a… - Overview of OSACT5 Shared Task on Arabic Offensive Language and Hate Speech Detection (2022 · 15 citations)
The paper reports on the OSACT5 shared task, which follows up OSACT4 and asks systems to find abusive content in Arabic tweets at three levels of detail. - Halwasa: Quantify and Analyze Hallucinations in Large Language Models: Arabic as a Case Study (2024 · 14 citations)
The paper addresses the lack of any resource for measuring LLM hallucination in Arabic. The authors built Halwasa, a 10K-sentence dataset generated by ChatGPT (gpt-3.5-turbo-0301) and GPT-4 (gpt-4-0314), with each model contributing half. - ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccination (2022 · 13 citations)
Public discussion of COVID-19 vaccines on Arabic Twitter mixed useful guidance with rumours and conspiracy content. - QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification (2019 · 13 citations)
The paper reports the QC-GO team's entry in the MADAR Shared Task on fine-grained Arabic dialect identification. - QCRI@QALB-2015 Shared Task: Correction of Arabic Text for Native and Non-Native Speakers' Errors (2015 · 12 citations)
The authors present the system QCRI entered in QALB-2015, a shared competition on automatically fixing errors in written Arabic. - Best Practices for Crowdsourcing Dialectal Arabic Speech Transcription (2015 · 11 citations)
Dialectal Arabic (DA) has no fixed spelling, so standard crowdsourcing quality checks break down when collecting speech transcripts. - ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic (2021 · 10 citations)
The authors address the lack of sizable, hand-labeled Arabic COVID-19 tweet data that could help governments track public concerns, requests, and harmful content such as rumors and bogus cures. - Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case Study (2023 · 9 citations)
The paper asks whether usable Arabic text-to-speech can be built without a studio corpus by reusing broadcast news collected for ASR.
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